AI for Medical Prognosis
Learn to apply machine learning for patient survival prediction and medical risk assessment using tree-based models.
Learn to apply machine learning for patient survival prediction and medical risk assessment using tree-based models.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full AI for Medicine Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(770 ratings)
27,972 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Build linear and tree-based prognostic models for patient outcomes
Evaluate model performance using concordance index
Handle missing medical data through various imputation techniques
Develop time-based survival prediction models
Implement risk assessment models for medical applications
Skills you'll gain
This course includes:
2.9 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on applying machine learning to medical prognosis, a branch of medicine specializing in predicting patient health outcomes. Students learn to build and evaluate prognostic models using decision trees and linear approaches. The curriculum covers handling missing medical data, working with survival data, and implementing both tree-based and linear risk models. Special emphasis is placed on practical applications in healthcare settings and evaluating model performance using medical-specific metrics.
Linear Prognostic Models
Module 1 · 8 Hours to complete
Prognosis with Tree-based Models
Module 2 · 7 Hours to complete
Survival Models and Time
Module 3 · 6 Hours to complete
Build a Risk Model Using Linear and Tree-based Models
Module 4 · 8 Hours to complete
Fee Structure
Instructors
AI Product Manager and Expert in AI Education
Eddy Shyu is a highly experienced AI Product Manager at Cisco, and was previously the Curriculum Product Manager at DeepLearning.AI. With a strong foundation in AI education and product management, Eddy has played a pivotal role in developing a wide range of online courses on Artificial Intelligence. Over the course of his career, Eddy has designed and built around 40 AI-focused online courses, which are available on prestigious platforms like Coursera, DeepLearning.AI, Udacity, and Cisco Networking Academy. His courses have reached thousands of learners globally, helping them master critical AI concepts and technologies.With a background in both AI education and AI product management, Eddy’s expertise bridges the gap between cutting-edge AI technologies and the needs of learners and businesses alike. His work at Cisco and DeepLearning.AI has enabled organizations and individuals to leverage AI for practical applications in various industries, particularly healthcare, technology, and business.
AI for Medicine Expert and Instructor at DeepLearning.AI
Pranav Rajpurkar is an Instructor at DeepLearning.AI and a leading researcher in the field of AI for Medicine. He is currently a faculty member at Harvard University in the Department of Biomedical Informatics, where his research focuses on leveraging artificial intelligence (AI) and machine learning to address key challenges in clinical medicine. By developing novel algorithms and datasets, Pranav aims to drive AI technologies that can assist in medical decision-making, improving outcomes and transforming the healthcare landscape.Pranav is widely recognized for his contribution to the intersection of AI and healthcare. He is the co-host of the AI Health Podcast and co-editor of the Doctor Penguin AI Health Newsletter, where he discusses the latest trends and advancements in AI applications in medicine. His expertise has made him a sought-after educator, and he has played a pivotal role in instructing the Coursera course series on AI for Medicine. He also founded the AI for Healthcare Bootcamp Program, helping to train professionals in the rapidly growing field of AI in healthcare.
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4.7 course rating
770 ratings
Frequently asked questions
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